AI-modellen kunnen met 99% zekerheid fout hebben

Artificial intelligence systems can express high certainty while delivering incorrect predictions, a phenomenon that undermines the reliability of confidence scores in machine learning models. This paradox highlights why developers must validate model outputs through independent testing rather than relying solely on internal confidence metrics.